• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2021.05a
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• pp.227-229
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• 2021

The modern society is advancing from the analog era to the digital imaging era, and in line with the trend of this era, various imaging devices such as exploration robots, medical equipment, and CCTV are helping our daily life a lot. However, noises caused by various causes in digital images not only cause image deterioration, but also deteriorate and deteriorate image quality. A typical noise is AWGN, and types of filters to remove it include an average filter, a median filter, and an alpha-trimmed average filter, but these filters have a disadvantage in that they show somewhat inadequate noise reduction performance in the high frequency region. Therefore, in this paper, a modified spatial division average filter based on standard deviation is proposed to effectively reduce AWGN existing in the high frequency region of the image.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2002.05a
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• pp.1077-1080
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• 2002

In building acoustics, reverberation time is an important acoustic parameter. However, it is often difficult to measure short reverberation times at low frequencies using the traditional band pass filter bank if the product of bandwidth (B) and reverberation time (T) is small. It is well known that the minimum permissible product of bandwidth and reverberation time of the traditional band pass filter is at least 16 ［F. Jacobsen, J. Sound Vib. 115, 163-170 (1987)]. This strict requirement makes it difficult to measure short reverberation times of an acoustic room at low frequencies exactly. In order to reduce this strict requirement, recently, the wavelet filter bank is developed and the minimum permissible product of bandwidth and reverberation time is replaced with 4 [S. K. Lee, J, Sound Vib. 252, 141-153 (2002)]. In the present paper, it is demonstrated how the short reverberation times at low frequencies are successfully measured by using the wavelet filter bank. In order to present this job, two synthetic signals and one measured signal are used for impulse responses of an acoustic room.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.17 no.11
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• pp.1264-1270
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• 1992

MF(Morphological filter) is generally composed of several morphological operation, which are the diverse structuring element. The two basic operation are erosion and dilation. The two other operation, opening and closing, are defined based on these two operation. Performance of open-closing(OC) is better exellent than close-opening(CO) to reduce noise of image data with Gaussian noise. In this paper, to use the hybrid median filter in processing the image, is shown that hybrid median filter has better results image quality than other filters, to analyze by computer simulation.

• Journal of the Korean Society of Radiology
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• v.13 no.5
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• pp.765-771
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• 2019

Noise in skull X-ray imaging is inevitable, which reduces imaging quality and diagnostic accuracy and increases errors due to the nature of digital imaging devices. Increasing the dose can attenuate noise, but that could lead to big problems with higher exposure dose received by patients. Thus, noise reduction algorithms are actively being studied at low doses to solve dose problems and reduce noise at the same time. Wiener filter and median filter have been widely used, with the disadvantages of poor noise reduction efficiency and loss of much information about imaging boundary. The purpose of this study is to apply total variation (TV) algorithm to skull X-ray imaging that can compensate for the problems of previous noise reduction efficiency to assess quantitatively and compare them. For this study, skull X-ray imaging is obtained using various kVp and mAs using the skull phantom using the X-ray device of Siemens. In addition, contrast to noise ratio (CNR) and coefficient of variation (COV) are compared and measured when noisy image, median filter, Wiener filter and TV algorithm were applied to each phantom imaging. Experiments showed that when TV algorithms were applied, CNR and COV characteristics were excellent under all conditions. In conclusion, we've been able to see if we can use TV algorithm to improve image quality and CNR could be seen to increase due to the decrease in noise as the amount of increased mAs. On the other hand, COV decreased as the amount of increased mAs, and when kVp increased, noise was reduced and the transmittance was increased, so COV was reduced.

• The Korean Journal of Applied Statistics
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• v.23 no.3
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• pp.595-607
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• 2010

This paper addresses the problem of reducing the speckle noise in SAR images by wavelet transformation, using a non-local means(NLM) filter originated for Gaussian noise removal. Log-transformed SAR image makes multiplicative speckle noise additive. Thus, non-local means filtering and wavelet thresholding are used to reduce the additive noise, followed by an exponential transformation. NLM filter is an image denoising method that replaces each pixel by a weighted average of all the similarly pixels in the image. But the NLM filter takes an acceptable amount of time to perform the process for all possible pairs of pixels. This paper, also proposes an alternative strategy that uses the t-test more efficiently to eliminate pixel pairs that are dissimilar. Extensive simulations showed that the proposed filter outperforms many existing filters terms of quantitative measures such as PSNR and DSSIM as well as qualitative judgments of image quality and the computational time required to restore images.

• Journal of the Korean Data and Information Science Society
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• v.20 no.5
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• pp.869-878
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• 2009

Image restoration techniques such as noise reduction and contrast enhancement have been researched for enhancing a contaminated image by the noise. An image degraded by additive random noise can be enhanced by noise reduction. Sigma filtering is one of the most widely used method to reduce the noise. In this paper, we propose a new sigma filter algorithm based on noise variance estimation which effectively enhances the degraded image by noise. Specifically, the Bartlett test is used to measure the degree of noise with respect to the degree of image feature. Simulation results are also given to show the performance of the proposed algorithm.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• v.2
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• pp.255-260
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• 2006

Safety-critical navigation systems have to provide 'reliable' position solutions, i.e., they must detect and exclude measurement or system faults and estimate the uncertainty of the solution. To obtain more accurate and reliable navigation systems, various filtering methods have been employed to reduce measurement noise level, or integrate sensors, such as global navigation satellite system/inertial navigation system (GNSS/INS) integration. Recently, particle filters have attracted attention, because they can deal with nonlinear/non-Gaussian systems. In most GNSS applications, the GNSS measurement noise is assumed to follow a Gaussian distribution, but this is not true. Therefore, we have proposed a fault detection and exclusion method using particle filters assuming non-Gaussian measurement noise. The performance of our method was contrasted with that of conventional Kalman filter methods with an assumed Gaussian noise. Since the Kalman filters presume that measurement noise follows a Gaussian distribution, they used an overbounded standard deviation to represent the measurement noise distribution, and since the overbound standard deviations were too conservative compared to the actual distributions, this degraded the integrity-monitoring performance of the filters. A simulation was performed to show the improvement in performance of our proposed particle filter method by not using the sigma overbounding. The results show that our method could detect smaller measurement biases and reduced the protection level by 30% versus the Kalman filter method based on an overbound sigma, which motivates us to use an actual noise model instead of the overbounding or improve the overbounding methods.

• Transactions of the Korean Society of Automotive Engineers
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• v.13 no.4
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• pp.152-159
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• 2005

The method of induction noise reduction can be classified by using passive control or active control method. However, the passive control method has a demerit to reduce the effect of noise reduction to low frequency (below) 500Hz) range and to be limited in a space of the engine room. Whereas, the active control method can overcome the demerit of passive control method. The algorithm of active control is mostly used in LMS (Least-Mean-Square) algorithm because it can obtain the complex transfer function easily in real-time. Especially, Filtered-X LMS (FXLMS) algorithm is applied to an ANC system. However, the convergence performance of LMS algorithm could not match if the FXLMS algorithm is applied to an active control of the induction noise under rapidly accelerated driving conditions. So, in order to solve the problem in this study, the Moving Bandpass Filter(MBPF) was proposed and implemented. The ANC using MBPF for the reduction of the induction noise shows that more noise reduction as 4dB than without MBPF.

• The Transactions of the Korean Institute of Electrical Engineers D
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• v.55 no.3
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• pp.138-141
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• 2006

Blood flow is one of vital signals related to human physiological information. Photoplethysmograph (PPG) has been used to measure indirectly heart rate, blood oxygen saturation ($SpO_2$), and so on. Because PPG signal is weak and sensitive to motion artifacts, it is very important to continuously obtain stable PPG signal during free movement. In this study, we applied the scaled Fourier linear combiner (SFLC) using both the adaptive filter and FLC to remove effectively the motion artifacts as well as background noise in the real time without additional signal correlated with motion from a accelerometer. The proposed method would be useful to reduce the movement and background noise which are not synchronized with heart rate.

• Proceedings of the Korea Electromagnetic Engineering Society Conference
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• 2003.11a
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• pp.155-159
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• 2003

This paper presents fully integrated 5 GHz band low phase noise LC tank VCO. The implemented VCO is tuned by integrated PN diode and tuning rage is $5.01{\sim}5.30$ GHz under $0{\sim}3 V$ control voltage. For good phase noise performance, LC filtering technique, common in Si CMOS process, is used, and to prevent degradation of phase noise performance by collector shot-noise and to reduce power dissipation the HBT is biased at low collector current density bias point. The measured phase noise is -87.8 dBc/Hz at 100 kHz offset frequency and -111.4 dBc/Hz at 1 MHz offset frequency which is good performance. Moreover phase noise is improved by roughly 5 dEc by LC filter. It is the first experimental result in InGaP/GaAs HBT process. The figure of merit of the fabricated VCO with LC filter is -172.1 dBc/Hz. It is the best result among 5 GHz InGaP HBT VCOs. Moreover this work shows lower DC power consumption, higher output power and more fixed output power compared with previous 4, 5 GHz band InGaP HBT VCOs.